Modern computing has allowed individuals to access vast amounts of data. In fact, the vastness of the data is such that is often difficult for users of the internet, computer systems, media centers, and the like to present or display data such that they can easily grasp relationships that may exist in the displayed data. This has led to the use of search engines and more specifically recommendation engines to help users sort through available data.
For example, presently there exist a variety of recommendation services and engines, which allow a user to express interest in a media item, such as a song, movie, television show, videogame, or the like. The recommendation service or engine takes this focus media item of interest as an input and then returns a group of related media items which have been determined in some fashion to be related to the focus media item that the user has expressed interest in. This group of related media items is typically displayed on a display device along with the focus media item in some fashion such as via a vertical listing.
In such a display, related items may or may not be displayed by order of relatedness to the focus media item, and may or may not display alphanumeric metadata indicating a level of relatedness to the focus media item. This leaves the user to manually sort through each result and somehow interpret its relatedness to the focus media item, either by viewing each displayed item and assigning a personal relevance to it, it or by interpreting displayed alphanumeric relatedness metadata. Such displays of a focus media item and related media items can be confusing and require a user to spend a considerable amount of time interpreting displayed information. This can frustrate a user's experience with a computing device, media device, or a recommendation engine.
Thus, a display of related media items which addresses some of the above disadvantages would be advantageous.